OpenAI is taking the first step in gradual deployment of GPTs – tailored ChatGPT for a specific purpose – for safety purposes.
SEO
A New Way To Monetize WordPress
Automattic, the company behind WordPress.com, Jetpack, WooCommerce and more, have announced a new program to woo Agencies into their ecosystem of products with more ways to earn revenue.
This new program could be seen as putting Automattic into direct competition with closed source systems like Wix and Duda but there are clear differences between all three products and services.
Automattic For Agencies
Automattic for Agencies brings together multiple Automattic products into a single service with a dashboard for managing multiple client sites and billing. The program offers a unified locations for managing client sites as well as discounted pricing and revenue sharing opportunities. Aside from the benefits of streamlining the program also offers technical support across all of the Automattic products that are a part of the program. Lastly the program offers agencies managed security and performance improvements.
According to the announcement:
“We worry about site performance and security so you don’t have to. When you connect your sites to the Automattic for Agencies dashboard, you’ll receive instant notifications about updates and alerts, so your sites stay problem-free and your clients stay happy.”
Revenue Share And Discounts
Agencies can now earn a revenue share of the Automattic products used by clients. For example, agencies can earn a 50% revenue share on Jetpack product referrals, including renewals. As part of the program Jetpack also offers discounts on licenses, starting at 10% off for five licenses and to as high as 50% off for 100 licenses.
As part of the new program there are similar benefits for agencies that build or manage WooCommerce sites, with discounted agency pricing and a referral program
WordPress.com, the managed WordPress hosting subsidiary of Automattic, is offering a 20% revenue share on new subscriptions and a 50% share on migrations from other hosts.
A tweet from WordPress.com described the new program:
“Agencies, we’ve got some news for you!
Our new referral program is live, and as a referrer of http://WordPress.com’s services, your agency will receive a 20% revenue share on new subscriptions and 50% on new migrations to http://WordPress.com from other hosting providers.”
New Directory For Agencies
A forthcoming benefit of the Autommatic For Agencies program is a business directory that lists agencies that are a part of the program. The benefit of the directory is presumably that it may lead to business referrals to the agencies.
The Jetpack announcement describes the new directory:
“Gain heightened visibility through multiple directory listings across Automattic’s business units. This increased exposure creates more opportunities for potential clients to find and engage with your services, helping you grow your agency’s reach and reputation.”
The WooCommerce announcement describes the directory like this:
“Expand your reach
Increase your visibility with partner directory listings across multiple Automattic brands.”
Automattic Affiliate Program
The Automattic for Agencies announcement follows the rollout of a separate affiliate program which offers up to 100% referral bonus for affiliates who refer new hosting clients, with a limit of $300 payout per item, and up to 50% referral bonus for Jetpack plugin subscriptions. The program has a 30 day cookie conversion period which provides affiliates the opportunity to earn referral bonuses on any additional sales within a 30 day period.
Read more about the new program:
Live the Suite Life With Automattic For Agencies
Featured Image by Shutterstock/Volodymyr TVERDOKHLIB
SEO
What Is Schema Markup & Why Is It Important For SEO?
Schema.org is a collection of vocabulary (or schemas) used to apply structured data markup to web pages and content. Correctly applying schema can improve SEO outcomes through rich snippets.
Structured data markup is translated by platforms such as Google and Microsoft to provide enhanced rich results (or rich snippets) in search engine results pages or emails. For example, you can markup your ecommerce product pages with variants schema to help Google understand product variations.
Schema.org is an independent project that has helped establish structured data consistency across the internet. It began collaborating with search engines such as Google, Yahoo, Bing, and Yandex back in 2011.
The Schema vocabulary can be applied to pages through encodings such as RDFa, Microdata, and JSON-LD. JSON-LD schema is preferred by Google as it is the easiest to apply and maintain.
Schema is not a ranking factor.
However, your webpage becomes eligible for rich snippets in SERPs only when you use schema markup. This can enhance your search visibility and increase CTR on your webpage from search results.
Schema can also be used to build a knowledge graph of entities and topics. Using semantic markup in this way aligns your website with how AI algorithms categorize entities, assisting search engines in understanding your website and content.
This means that search engines should have additional information to help them figure out what the webpage is about.
You can even link your entities directly to sites like Wikipedia or Google’s knowledge graph to build explicit connections. Using Schema this way can have positive SEO results, according to Martha van Berkel, CEO of Schema App:
By helping search engines understand content, you are assisting them in saving resources (especially important when you have a large website with millions of pages) and increasing the chances for your content to be interpreted properly and ranked well. While this may not be a ranking factor directly, Schema helps your SEO efforts by giving search engines the best chance of interpreting your content correctly, giving users the best chance of discovering it.
Listed above are some of the most popular uses of schema, which are supported by Google and other search engines.
You may have an object type that has a schema.org definition but is not supported by search engines.
In such cases, it is advised to implement them, as search engines may start supporting them in the future, and you may benefit from them as you already have that implementation.
Google recommends JSON-LD as the preferred format for structured data. Microdata is still supported, but JSON-LD schema is recommended.
In certain circumstances, it isn’t possible to implement JSON-LD schema due to website technical infrastructure limitations such as old content management systems). In these cases, the only option is to markup HTML via Microdata or RDFa.
You can now mix JSON-LD and Microdata formats by matching the @id attribute of JSON-LD schema with the itemid attribute of Microdata schema. This approach helps reduce the HTML size of your pages.
For example, in a FAQ section with extensive text, you can use Microdata for the content and JSON-LD for the structured data without duplicating the text, thus avoiding an increase in page size. We will dive deeper into this below in the article when discussing each type in detail.
JSON-LD encodes data using JSON, making it easy to integrate structured data into web pages. JSON-LD allows connecting different schema types using a graph with @ids, improving data integration and reducing redundancy.
Let’s look at an example. Let’s say that you own a store that sells high-quality routers. If you were to look at the source code of your homepage, you would likely see something like this:
Once you dive into the code, you’ll want to find the portion of your webpage that discusses what your business offers. In this example, that data can be found between the two
tags.
The following JSON-LD formatted text will markup the information within that HTML fragment on your webpage, which you may want to include in your webpage’s
section.
This snippet of code defines your business as a store via the attribute"@type": "Store".
Then, it details its location, contact information, hours of operation from Monday to Saturday, and different operational hours for Sunday.
By structuring your webpage data this way, you provide critical information directly to search engines, which can improve how they index and display your site in search results. Just like adding tags in the initial HTML, inserting this JSON-LD script tells search engines specific aspects of your business.
Let’s review another example of WebPage schema connected with Organization and Author schemas via @id. JSON-LD is the format Google recommends and other search engines because it’s extremely flexible, and this is a great example.
In the example:
- Website links to the organization as the publisher with
@id. - The organization is described with detailed properties.
- WebPage links to the WebSite with
isPartOf. - NewsArticle links to the WebPage with
isPartOf, and back to the WebPage withmainEntityOfPage, and includes the author property via@id.
You can see how graph nodes are linked to each other using the"@id"attribute. This way, we inform Google that it is a webpage published by the publisher described in the schema.
The use of hashes (#) for IDs is optional. You should only ensure that different schema types don’t have the same ID by accident. Adding custom hashes (#) can be helpful, as it provides an extra layer of insurance that they will not be repeated.
You may wonder why we use"@id"to connect graph nodes. Can’t we just drop organization, author, and webpage schemas separately on the same page, and it is intuitive that those are connected?
The issue is that Google and other search engines cannot reliably interpret these connections unless explicitly linked using @id.
Adding to the graph additional schema types is as easy as constructing Lego bricks. Say we want to add an image to the schema:
{
"@type": "ImageObject",
"@id": "https://www.example.com/#post-image",
"url": "https://www.example.com/example.png",
"contentUrl": "https://www.example.com/example.png",
"width": 2160,
"height": 1215,
"thumbnail": [
{
"@type": "ImageObject",
"url": "https://example.com/4x3/photo.jpg",
"width": 1620,
"height": 1215
},
{
"@type": "ImageObject",
"url": "https://example.com/16x9/photo.jpg",
"width": 1440,
"height": 810
},
{
"@type": "ImageObject",
"url": "https://example.com/1x1/photo.jpg",
"width": 1000,
"height": 1000
}
]
}As you already know from the NewsArticle schema, you need to add it to the above schema graph as a parent node and link via @id.
As you do that, it will have this structure:
Quite easy, isn’t it? Now that you understand the main principle, you can build your own schema based on the content you have on your website.
And since we live in the age of AI, you may also want to use ChatGPT or other chatbots to help you build any schema you want.
2. Microdata Schema Format
Microdata is a set of tags that aims to make annotating HTML elements with machine-readable tags much easier.
However, the one downside to using Microdata is that you have to mark every individual item within the body of your webpage. As you can imagine, this can quickly get messy.
Take a look at this sample HTML code, which corresponds to the above JSON schema with NewsArticle:
Our Company
Example Company, also known as Example Co., is a leading innovator in the tech industry.
Founded in 2000, we have grown to a team of 200 dedicated employees.
Our slogan is: "Innovation at its best".
Contact us at +1-800-555-1212 for customer service.
Our Founder
Our founder, Jane Smith, is a pioneer in the tech industry.
About Us
This is the About Us page for Example Company.
Example News Headline
This is an example news article.
This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.
Author: John Doe. Connect with John on Twitter and LinkedIn.
If we convert the above JSON-LD schema into Microdata format, it will look like this:
Our Company
Example Company, also known as
Example Co., is a leading innovator in the tech industry.
Founded in
2000-01-01, we have grown to a team of
200 dedicated employees.
Our slogan is: Innovation at its best.
Contact us at
+1-800-555-1212 for
Customer Service.
https://www.example.com
About Us
This is the About Us page for Example Company.
https://www.example.com/about
Example News Headline
This is an example news article.
This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.
Author:
John Doe
Profile
Twitter
LinkedIn
This example shows how complicated it becomes compared to JSON-LD since the markup is spread over HTML. Let’s understand what is in the markup.
You can see
tags like:
By adding this tag, we’re stating that the HTML code contained between the
blocks identifies a specific item.
Next, we have to identify what that item is by using the ‘itemtype’ attribute to identify the type of item (Person).
An item type comes in the form of a URL (such as https://schema.org/Person). Let’s say, for example, you have a product you may use http://schema.org/Product.
To make things easier, you can browse a list of item types here and view extensions to identify the specific entity you’re looking for. Keep in mind that this list is not all-encompassing but only includes ones that are supported by Google, so there is a possibility that you won’t find the item type for your specific niche.
It may look complicated, but Schema.org provides examples of how to use the different item types so you can see what the code is supposed to do.
Don’t worry; you won’t be left out in the cold trying to figure this out on your own!
If you’re still feeling a little intimidated by the code, Google’s Structured Data Markup Helper makes it super easy to tag your webpages.
To use this amazing tool, just select your item type, paste in the URL of the target page or the content you want to target, and then highlight the different elements so that you can tag them.
3. RDFa Schema Format
RDFa is an acronym for Resource Description Framework in Attributes. Essentially, RDFa is an extension to HTML5 designed to aid users in marking up structured data.
RDFa isn’t much different from Microdata. RDFa tags incorporate the preexisting HTML code in the body of your webpage. For familiarity, we’ll look at the same code above.
The HTML for the same JSON-LD news article will look like:
vocab="https://schema.org/" typeof="WebSite" resource="https://www.example.com/#website">
Our Company
Example Company, also known as
Example Co., is a leading innovator in the tech industry.
Founded in
2000-01-01, we have grown to a team of
200 dedicated employees.
Our slogan is: Innovation at its best.
Contact us at
+1-800-555-1212 for
Customer Service.
https://www.example.com
About Us
This is the About Us page for Example Company.
https://www.example.com/about
Example News Headline
This is an example news article.
This is the full content of the example news article. It provides detailed information about the news event or topic covered in the article.
Author:
John Doe
Profile
Twitter
LinkedIn
Unlike Microdata, which uses a URL to identify types, RDFa uses one or more words to classify types.
vocab=”http://schema.org/” typeof=”WebPage”>
If you wish to identify a property further, use the ‘typeof’ attribute.
Let’s compare JSON-LD, Microdata, and RDFa side by side. The @type attribute of JSON-LD is equivalent to the itemtype attribute of Microdata format and the typeof attribute in RDFa. Furthermore, the propertyName of JSON-LD attribute would be the equivalent of the itemprop and property attributes.
Attribute Name
JSON-LD
Microdata
RDFa
Type
@type
itemtype
typeof
ID
@id
itemid
resource
Property
propertyName
itemprop
property
Name
name
itemprop=”name”
property=”name”
Description
description
itemprop=”description”
property=”description”
For further explanation, you can visit Schema.org to check lists and view examples. You can find which kinds of elements are defined as properties and which are defined as types.
To help, every page on Schema.org provides examples of how to apply tags properly. Of course, you can also fall back on Google’s Structured Data Testing Tool.
4. Mixing Different Formats Of Structured Data With JSON-LD
If you use JSON-LD schema but certain parts of pages aren’t compatible with it, you can mix schema formats by linking them via @id.
For example, if you have live blogging on the website and a JSON-LD schema, including all live blogging items in the JSON schema would mean having the same content twice on the page, which may increase HTML size and affect First Contentful Paint and Largest Contentful Paint page speed metrics.
You can solve this either by generating JSON-LD dynamically with JavaScript when the page loads or by marking up HTML tags of live blogging via the Microdata format, then linking to your JSON-LD schema in the head section via “@id“.
Here is an example of how to do it.
Say we have this HTML with Microdata markup with itemid="https://www.example.com/live-blog-page/#live-blog"
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We can link to it from the sample JSON-LD example we had like this:
If you copy and paste HTML and JSON examples underneath in the schema validator tool, you will see that they are validating properly.
The schema validator does validate the above example.
The SEO Impact Of Structured Data
This article explored the different schema encoding types and all the nuances regarding structured data implementation.
Schema is much easier to apply than it seems, and it’s a best practice you must incorporate into your webpages. While you won’t receive a direct boost in your SEO rankings for implementing Schema, it can:
- Make your pages eligible to appear in rich results.
- Ensure your pages get seen by the right users more often.
- Avoid confusion and ambiguity.
The work may seem tedious. However, given time and effort, properly implementing Schema markup is good for your website and can lead to better user journeys through the accuracy of information you’re supplying to search engines.
Image Credits
Featured Image: Paulo Bobita
Screenshot taken by author
Read more:
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Advanced Technical SEO: A Complete Guide
SEO
Gen Z Ditches Google, Turns To Reddit For Product Searches
A new report from Reddit, in collaboration with GWI and AmbassCo, sheds light on the evolving search behaviors of Generation Z consumers.
The study surveyed over 3,000 internet users across the UK, US, and Germany, highlighting significant changes in how young people discover and research products online.
Here’s an overview of key findings and the implications for marketers.
Decline In Traditional Search
The study found that Gen Z uses search engines to find new brands and products less often.
That’s because they shop online differently. They’re less interested in looking for expert reviews or spending much time searching for products.
There are also frustrations with mobile-friendliness and complex interfaces on traditional search platforms.
Because of this, traditional SEO strategies might not work well for reaching younger customers.
Takeaway
Companies trying to reach Gen Z might need to try new methods instead of just focusing on being visible on Google and other search engines.
Rise Of Social Media Discovery
Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.
Gen Z is increasingly using social media to find new brands and products.
The study shows that Gen Z has used social media for product discovery 36% more frequently since 2018.
This change is affecting how young people shop online. Instead of searching for products, they expect brands to appear in their social media feeds.
Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.Because of this, companies trying to reach young customers need to pay more attention to how they present themselves on social media.
Takeaway
To succeed at marketing to Gen Z, businesses will likely need to focus on two main things:
- Ensure that your content appears more often in social media feeds.
- Create posts people want to share and interact with.
Trust Issues With Influencer Marketing
Even though more people are finding products through social media, the report shows that Gen Z is less likely to trust what social media influencers recommend.
These young shoppers often don’t believe in posts that influencers are paid to make or products they promote.
Instead, they prefer to get information from sources that feel more real and are driven by regular people in online communities.
Takeaway
Because of this lack of trust, companies must focus on being genuine and building trust when they try to get their websites to appear in search results or create ads.
Some good ways to connect with these young consumers might be to use content created by regular users, encourage honest product reviews, and create authentic conversations within online communities.
Challenges With Current Search Experiences
The research shows that many people are unhappy with how search engines work right now.
More than 60% of those surveyed want search results to be more trustworthy. Almost half of users don’t like looking through many search result pages.
Gen Z is particularly bothered by inaccurate information and unreliable reviews.
Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.Takeaway
Given the frustration with search quality, marketers should prioritize creating accurate, trustworthy content.
This can help build brand credibility, leading to more direct visits.
Reddit: A Trusted Alternative
The report suggests that Gen Z trusts Reddit when looking up products—it’s their third most trusted source, after friends and family and review websites.
Screenshot from Reddit study titled: “From search to research: How search marketers can keep up with Gen Z.”, June 2024.Young users like Reddit because it’s community-based and provides specific answers to users’ questions, making it feel more real.
It’s worth noting that this report comes from Reddit itself, which probably influenced why it’s suggesting its own platform.
Takeaway
Companies should focus more on being part of smaller, specific online groups frequented by Gen Z.
That could include Reddit or any other forum.
Why SEJ Cares
As young people change how they look for information online, this study gives businesses important clues about connecting with future customers.
Here’s what to remember:
- Traditional search engine use is declining among Gen Z.
- Social media is increasingly vital for product discovery.
- There’s growing skepticism towards influencer marketing.
- Current search experiences often fail to meet user expectations.
- Community-based platforms like Reddit are gaining trust.
Featured Image: rafapress/Shutterstock
SEO
Google Clarifies Organization Merchant Returns Structured Data
Google quietly updated their organization structured data documentation in order to clarify two points about merchant returns in response to feedback about an ambiguity in the previous version.
Organization Structured Data and Merchant Returns
Google recently expanded their Organization structured data so that it could now accommodate a merchant return policy. The change added support for adding a sitewide merchant return policy.
The original reason for adding this support:
“Adding support for Organization-level return policies
What: Added documentation on how to specify a general return policy for an Organization as a whole.
Why: This makes it easier to define and maintain general return policies for an entire site.”
However that change left unanswered about what will happen if a site has a sitewide return policy but also has a different policy for individual products.
The clarification applies for the specific scenario of when a site uses both a sitewide return policy in their structured data and another one for specific products.
What Takes Precedence?
What happens if a merchant uses both a sitewide and product return structured data? Google’s new documentation states that Google will ignore the sitewide product return policy in favor of a more granular product-level policy in the structured data.
The clarification states:
“If you choose to provide both organization-level and product-level return policy markup, Google defaults to the product-level return policy markup.”
Change Reflected Elsewhere
Google also updated the documentation to reflect the scenario of the use of two levels of merchant return policies in another section that discusses whether structured data or merchant feed data takes precedence. There is no change to the policy, merchant center data still takes precedence.
This is the old documentation:
“If you choose to use both markup and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”
This is the same section but updated with additional wording:
“If you choose to use both markup (whether at the organization-level or product-level, or both) and settings in Merchant Center, Google will only use the information provided in Merchant Center for any products submitted in your Merchant Center product feeds, including automated feeds.”
Read the newly updated Organization structured data documentation:
Organization (Organization) structured data – MerchantReturnPolicy
Featured Image by Shutterstock/sutlafk
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